In a typical wireless communication network, wireless devices, also known as wireless communication devices, mobile stations, stations (STA) and/or user equipments (UE), communicate via a Radio Access Network (RAN) to one or more core networks (CN). The RAN covers a geographical area which is divided into service areas or cell areas, which may also be referred to as a beam or a beam group, with each service area or cell area being served by a radio network node such as a radio access node e.g., a Wi-Fi access point or a radio base station (RBS), which in some networks may also be denoted, for example, a “NodeB” or “eNodeB”. A service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node communicates over an air interface operating on radio frequencies with the wireless device within range of the radio network node.
A Universal Mobile Telecommunications System (UMTS) is a third generation (3G) telecommunication network, which evolved from the second generation (2G) Global System for Mobile Communications (GSM). The UMTS terrestrial radio access network (UTRAN) is essentially a RAN using wideband code division multiple access (WCDMA) and/or High Speed Packet Access (HSPA) for user equipments. In a forum known as the Third Generation Partnership Project (3GPP), telecommunications suppliers propose and agree upon standards for third generation networks, and investigate enhanced data rate and radio capacity. In some RANs, e.g. as in UMTS, several radio network nodes may be connected, e.g., by landlines or microwave, to a controller node, such as a radio network controller (RNC) or a base station controller (BSC), which supervises and coordinates various activities of the plural radio network nodes connected thereto. This type of connection is sometimes referred to as a backhaul connection. The RNCs and BSCs are typically connected to one or more core networks.
Specifications for the Evolved Packet System (EPS), also called a Fourth Generation (4G) network, have been completed within 3GPP and this work continues in the coming 3GPP releases, for example to specify a Fifth Generation (5G) network. The EPS comprises the Evolved Universal Terrestrial Radio Access Network (E-UTRAN), also known as the Long Term Evolution (LTE) radio access network, and the Evolved Packet Core (EPC), also known as System Architecture Evolution (SAE) core network. E-UTRAN/LTE is a variant of a 3GPP radio access network wherein the radio network nodes are directly connected to the EPC core network rather than to RNCs. In general, in E-UTRAN/LTE the functions of an RNC are distributed between the radio network nodes, e.g. eNodeBs in LTE, and the core network. As such, the RAN of an EPS has an essentially “flat” architecture comprising radio network nodes connected directly to one or more core networks, i.e. they are not connected to RNCs. To compensate for that, the E-UTRAN specification defines a direct interface between the radio network nodes, this interface being denoted the X2 interface.
Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a Multiple-Input Multiple-Output (MIMO) communication channel. Such systems and/or related techniques are commonly referred to as MIMO.
To meet traffic demands in future wireless communication systems, new frequency bands are considered, for example in the range of 30-100 GHz. These bands offer wide spectrum for high data rate communications, however, the coverage range is limited because of the system and channel characteristics at such high frequencies. The use of MIMO beamforming technologies may allow overcoming the range limitations. With appropriate transmit and receive strategies, the antenna gain offered by the arrays may substantially improve the range coverage. An example strategy is when the beamforming is applied at the transmitter side to focus the transmitted power in a certain direction thereby increasing the gain and thus improving the quality of the communication between the transmitter and receiver. In Noh, Song, Michael D. Zoltowski, and David J. Love. “Multi-resolution codebook and adaptive beamforming sequence design for millimeter wave beam alignment.” (2015), beamforming using fixed codebooks or predefined beams is investigated to choose the best beam pair between the transmitter and receiver to achieve the best performance. With the available directional beams, the best transmitter and receiver pair of beams is given by the beam pair that is more aligned, which is referred to as beam alignment. (See references Noh, Song, Michael D. Zoltowski, and David J. Love. “Multi-resolution codebook and adaptive beamforming sequence design for millimeter wave beam alignment.” (2015), and J. Song, J. Choi, and D. J. Love, “Codebook design for hybrid beamforming in millimeter wave systems,” in Proc. IEEE Int. Conf. on Commun., London, UK, June 2015). Beam alignment may be used to avoid estimating the channel directly when very large numbers of transmitter and receiver antenna elements are considered. Such a direct estimation of the channel is costly since the number of channel parameters may be large. However, beam alignment methods often involve an exhaustive search over all possible pairs of beams to find the best beams for transmission based on some measure, e.g., signal-to-noise ratio (SNR). Such an exhaustive search may be also costly to perform before an upcoming communication especially with large number of antennas at the transmitter and receiver. In Noh, Song, Michael D. Zoltowski, and David J. Love. “Multi-resolution codebook and adaptive beamforming sequence design for millimeter wave beam alignment.” (2015), and J. Song, J. Choi, and D. J. Love, “Codebook design for hybrid beamforming in millimeter wave systems,” in Proc. IEEE Int. Conf. on Commun., London, UK June 2015, finding faster ways to perform this alignment has been investigated by exploiting system and channel characteristics to derive complex searching algorithms and to better focus the direction of the beams to achieve better performance. However, a problem with such approaches is the lack of beam search flexibility that is limited by rules defined by the codebook, and further, there may be a need for full channel knowledge which is costly.